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  • 1.
    Brügger, Annina
    et al.
    Department of Geography, University of Zurich, Switzerland.
    Richter, Kai-Florian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Fabrikant, Sara Irina
    Department of Geography, University of Zurich, Switzerland.
    Distributing Attention Between Environment and Navigation System to Increase Spatial Knowledge Acquisition During Assisted Wayfinding2018In: Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017) / [ed] Fogliaroni P., Ballatore A., Clementini E., Springer, 2018, p. 19-22Conference paper (Refereed)
    Abstract [en]

    Travelers happily follow the route instructions of their devices when navigating in an unknown environment. Navigation systems focus on route instructions to allow the user to efficiently reach a destination, but their increased use also has negative consequences. We argue that the limitation for spatial knowledge acquisition is grounded in the system’s design, primarily aimed at increasing navigation efficiency. Therefore, we empirically investigate how navigation systems could guide users’ attention to support spatial knowledge acquisition during efficient route following tasks.

  • 2.
    Brügger, Annina
    et al.
    University of Zurich, Switzerland.
    Richter, Kai-Florian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Fabrikant, Sara Irina
    University of Zurich, Switzerland.
    How does navigation system behavior influence human behavior?2019In: Cognitive Research: Principles and Implications, E-ISSN 2365-7464, Vol. 4, no 5Article in journal (Refereed)
    Abstract [en]

    Navigation systems are ubiquitous tools to assist wayfinders of the mobile information society with various navigational tasks. Whenever such systems assist with self-localization and path planning, they reduce human effort for navigating. Automated navigation assistance benefits navigation performance, but research seems to show that it negatively affects attention to environment properties, spatial knowledge acquisition, and retention of spatial information. Very little is known about how to design navigation systems for pedestrian navigation that increase both navigation performance and spatial knowledge acquisition. To this end, we empirically tested participants (N = 64) using four different navigation system behaviors (between-subject design). Two cognitive processes with varying levels of automation, self-localization and allocation of attention, define navigation system behaviors: either the system automatically executes one of the processes (high level of automation), or the system leaves the decision of when and where to execute the process to the navigator (low level of automation). In two experimental phases, we applied a novel empirical framework for evaluating spatial knowledge acquisition in a real-world outdoor urban environment. First, participants followed a route assisted by a navigation system and, simultaneously, incidentally acquired spatial knowledge. Second, participants reversed the route using the spatial knowledge acquired during the assisted phase, this time without the aid of the navigation system. Results of the route-following phase did not reveal differences in navigation performance across groups using different navigation system behaviors. However, participants using systems with higher levels of automation seemed not to acquire enough spatial knowledge to reverse the route without navigation errors. Furthermore, employing novel methods to analyze mobile eye tracking data revealed distinct patterns of human gaze behavior over time and space. We thus can demonstrate how to increase spatial knowledge acquisition without harming navigation performance when using navigation systems, and how to influence human navigation behavior with varying navigation system behavior. Thus, we provide key findings for the design of intelligent automated navigation systems in real-world scenarios.

  • 3.
    Kashian, Alireza
    et al.
    Dept. of Infrastructure Engineering, University of Melbourne, Parkville, Australia.
    Rajabifard, Abbas
    Dept. of Infrastructure Engineering, University of Melbourne, Parkville, Australia.
    Chen, Yiqun
    Dept. of Infrastructure Engineering, University of Melbourne, Parkville, Australia.
    Richter, Kai-Florian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    OSM POI Analyzer: A Platform for Assessing Position of POIs in OpenStreetMap2017In: ISPRS Geospatial Week 2017 / [ed] D. Li, J. Gong, B. Yang, H. Wu, L. Wu, Z. Gui, X. Cheng, H. Wu, S. Li, R. Lindenbergh, J. Boehm, M. Rutzinger, W. Yao, M. Weinmann, Z. Kang, K. Khoshelham, M. Peter, L. Díaz-Vilariño, W. Shi, B. Lu, H. Abdulmuttalib, M. R. Delavar, T. Balz, B. Osmanoglu, F. Rocca, U. Sörgel, J. Zhang, P. Li, S. Du, L. Zhao, X. Lin, K. Qin, C. Kang, X. Li, C. Chen, R. Li, G. Qiao, H. Wu, and C. Heipke, 2017, Vol. XLII-2/W7, p. 497-504Conference paper (Refereed)
    Abstract [en]

     In recent years, more and increased participation in Volunteered Geographical Information (VGI) projects provides enough data coverage for most places around the world for ordinary mapping and navigation purposes, however, the positional credibility of contributed data becomes more and more important to bring a long-term trust in VGI data. Today, it is hard to draw a definite traditional boundary between the authoritative map producers and the public map consumers and we observe that more and more volunteers are joining crowdsourcing activities for collecting geodata, which might result in higher rates of man-made mistakes in open map projects such as OpenStreetMap. While there are some methods for monitoring the accuracy and consistency of the created data, there is still a lack of advanced systems to automatically discover misplaced objects on the map. One feature type which is contributed daily to OSM is Point of Interest (POI). In order to understand how likely it is that a newly added POI represents a genuine real-world feature scientific means to calculate a probability of such a POI existing at that specific position is needed. This paper reports on a new analytic tool which dives into OSM data and finds co-existence patterns between one specific POI and its surrounding objects such as roads, parks and buildings. The platform uses a distance-based classification technique to find relationships among objects and tries to identify the high-frequency association patterns among each category of objects. Using such method, for each newly added POI, a probabilistic score would be generated, and the low scored POIs can be highlighted for editors for a manual check. The same scoring method can be used for existing registered POIs to check if they are located correctly. For a sample study, this paper reports on the evaluation of 800 pre-registered ATMs in Paris with associated scores to understand how outliers and fake entries could be detected automatically.

  • 4.
    Kashian, Alireza
    et al.
    University of Melbourne, Australia.
    Rajabifard, Abbas
    University of Melbourne, Australia.
    Richter, Kai-Florian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Chen, Yiqun
    University of Melbourne, Australia.
    Automatic analysis of positional plausibility for points of interest in OpenStreetMap using coexistence patterns2019In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 33, no 7, p. 1420-1443Article in journal (Refereed)
    Abstract [en]

    In the past decade, Volunteered Geographic Information (VGI) has emerged as a new source of geographic information, making it a cheap and universal competitor to existing authoritative data sources. The growing popularity of VGI platforms, such as OpenStreetMap (OSM), would trigger malicious activities such as vandalism or spam. Similarly, wrong entries by unexperienced contributors adds to the complexities and directly impact the reliability of such databases. While there are some existing methods and tools for monitoring OSM data quality, there is still a lack of advanced mechanisms for automatic validation. This paper presents a new recommender tool which evaluates the positional plausibility of incoming POI registrations in OSM by generating near real-time validation scores. Similar to machine learning techniques, the tool discovers, stores and reapplies binary distance-based coexistence patterns between one specific POI and its surrounding objects. To clarify the idea, basic concepts about analysing coexistence patterns including design methodology and algorithms are covered in this context. Furthermore, the results of two case studies are presented to demonstrate the analytical power and reliability of the proposed technique. The encouraging results of this new recommendation tool elevates the need for developing reliable quality assurance systems in OSM and other VGI projects.

  • 5.
    Kübler, Isabella
    et al.
    Department of Geography, University of Zürich.
    Richter, Kai-Florian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Fabrikant, Sara Irina
    Department of Geography, University of Zürich.
    How does the visualization of uncertainty influence decision making with hazard prediction maps?2017Other (Other academic)
    Abstract [en]

    A wealth of design strategies has been proposed by an interdisciplinary scientific community to visually communicate data uncertainty in maps, with the aim to support spatio-temporal decision-making under uncertainty (MacEachren et al., 2012). However, very few researchers have looked at whether and how uncertainty depictions might influence people’s reasoning processes and decision making outcomes, especially in problem contexts for which uncertainty truly matters, i.e., in life-threatening situations, or for dilemmatic decisions. We report on a map-based multi-criteria decision making study where participants (N=35) were asked to imagine purchasing a house shown on map stimuli inspired by Swiss National hazard prediction maps (SFOEN, 2016). These area-classed maps show the probability and intensity of natural disasters occurring in areas with varying danger levels in a pre-defined color scheme (i.e., red=high, blue=moderate, and yellow=low danger). Current hazard prediction maps do not depict prediction uncertainties, even though suggestions have been proposed in the cartographic literature (Kunz and Hurni, 2011). However, because there are uncertainties associated with the areal extent of the classed danger zones, we modified the zonal boundaries to show this locational uncertainty using the visual variables color value, focus, and texture, as suggested by prior empirical research (MacEachren, 2012). In a within-subject design, participants were repeatedly asked to decide which house they wished to buy, given varying house location characteristics, and respective purchase price information. The houses were depicted on a series of hazard prediction maps showing an area unknown to participants, with/without data uncertainty depicted. The maps showing uncertainty varied in the visual variables (i.e., color value|focus|texture) used to convey the locational uncertainty of the zonal boundaries. We recorded participants’ house selections, response times, and eye movements during the experiment. The task asked for participants’ preferences; there were no right or wrong answers. As hypothesized, our results show that participants’ decision making outcomes were indeed influenced by the depicted uncertainty information. Participants decided to buy different houses, as they weighted selection criteria differently, depending on whether uncertainty was shown on the map or not. We thus provide rare evidence on how uncertainty and the type of uncertainty visualization (i.e., varying color value, focus, or texture) can influence people’s reasoning to arrive at a complex, multi-criteria-based decision. We also find that participants’ individual differences with respect to their risk taking behavior tested with a standardised questionnaire influences their decision making. Risk takers underestimate the dangers of natural hazards when prediction uncertainties are depicted. With this unique study we are able to shed additional light on how people use visualized uncertainty information to make complex map-based decisions. Echoing Hegarty et al.'s (2016) findings, we again demonstrate that not only display design characteristics are relevant for map-based reasoning and decision making outcomes, but also the decision makers’ individual background, and the map-based decision-making task and context. References: Hegarty, M., Friedman, A., Boone, A.P., Barrett, T.J. (2016). Where Are You? The Effect of Uncertainty and Its Visual Representation on Location Judgments in GPS-Like Displays. Journal of Experimental Psychology, Applied, DOI: 10.1037/xap0000103. Kunz, M. and Hurni, L. (2011). How to Enhance Cartographic Visualisations of Natural Hazards Assessment Results. The Cartographic Journal, 48(1): 60-71. MacEachren, A. M., Roth, R. E., O'Brien, J., Li, B., Swingley, D., Gahegan, M. (2012). Visual Semiotics & Uncertainty Visualization: An Empirical Study. IEEE Transactions on Visualization and Computer Graphics, 18(12): 2496-2505. Swiss Federal Office for the Environment (SFOEN). Gefahrenkarten, Intensitätskarten und Gefahrenhinweiskarten. (Natural Hazard Maps), http://www.bafu.admin.ch/naturgefahren/14186/14801/15746/ (not available in English, accessed Oct. 2016).

  • 6.
    Rabe, Sven-Erik
    et al.
    Institute for Spatial and Landscape Planning, ETH Zurich, Switzerland.
    Gantenbein, Remo
    Department of Geography, University of Zurich, Switzerland.
    Richter, Kai-Florian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Grêt-Regamey, Adrienne
    Institute for Spatial and Landscape Planning, ETH Zurich, Switzerland.
    Increasing the credibility of expert-based models with preference surveys: mapping recreation in the riverine zone2018In: Ecosystem Services, ISSN 2212-0416, E-ISSN 2212-0416, Vol. 31, p. 308-317Article in journal (Refereed)
    Abstract [en]

    Recreation is a basic human need and therefore must be considered in spatial planning, which requires spatially explicit mapping of the recreation suitability of a landscape. The current methods for this type of mapping have limitations: On one hand, widely used expert-based models for large scale suitability assessments often suffer from discrepancies between the mapped values from expert assessment and actual user preferences. On the other hand, elicitation of personal preferences of potential users is complex and time-consuming, and their applicability to larger scales is limited.

    In this paper, we demonstrate the development of a spatially explicit model for the recreation suitability of the riverine zone that integrates the preferences of the users with an expert-based modeling process. First, we conducted an analytic hierarchy process (AHP) with experts to generate four different model variants based on physical variables. These model variants differ in terms of the strength of the influence of the variables on the recreation suitability. Second, an online survey was used to gather data on user preferences for various river sections with regard to recreation. A comparison of the expert model results with the preferences of the potential users shows a clear correlation between one model variant and the users’ preferences. This result suggests that it is possible to elaborate an expert model which corresponds to the preferences of users.

    We made the model results available for the planning and development of the riverine zone in the canton of Zurich. To this end, they were integrated in a decision support platform together with other planning-relevant information.

  • 7.
    Richter, Kai-Florian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Identifying Landmark Candidates Beyond Toy Examples: A Critical Discussion and Some Way Forward2017In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 31, no 2, p. 135-139Article in journal (Refereed)
    Abstract [en]

    Incorporating references to landmarks in navigation systems requires having data on potential landmarks in the first place. While there have been many approaches in the scientific literature for identifying landmark candidates, these have hardly been picked up in actual, running systems. One major obstacle for this to happen may be that most—if not all—approaches presented so far are not scalable due to their underlying data requirements. In this paper, I will critically discuss existing approaches in light of their scalability. I will then suggest a way forward to more scalable solutions by combining in a smart way aspects of different approaches.

  • 8.
    Richter, Kai-Florian
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Horned, Arvid
    Umeå University.
    Karlsson, Kristoffer
    Umeå University.
    Icon-based Navigation2018In: Geospatial Technologies for All: short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science / [ed] Mansourian, A., Pilesjö, P., Harrie, L., von Lammeren, R, Lund: Lund University , 2018, article id 86Conference paper (Refereed)
    Abstract [en]

    Icon-based navigation uses a minimalist approach to mobile navigation assistance by offering navigators only icon displays representing landmark objects at waypoints along a route in an indoor environment. In this paper, we motivate this new concept and its usefulness, present a first prototype implementation exploring the concept, and results of an initial empirical evaluation. While results are not fully conclusive, they point to the potential of this kind of navigation assistance.

  • 9.
    Thrash, Tyler
    et al.
    University of Zürich, Switzerland.
    Lanini-Maggi, Sara
    University of Zürich, Switzerland.
    Fabrikant, Sara I.
    University of Zürich, Switzerland.
    Bertel, Sven
    Hochschule Flensburg, Germany.
    Brügger, Annina
    University of Zürich, Switzerland.
    Crede, Sascha
    University of Zürich, Switzerland.
    Do, Cao Tri
    University of Zürich / ETH Zürich, Switzerland.
    Gartner, Georg
    TU Wien, Austria.
    Huang, Haosheng
    University of Zürich, Switzerland.
    Münzer, Stefan
    Universität Mannheim, Germany.
    Richter, Kai-Florian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    The Future of Geographic Information Displays from GIScience, Cartographic, and Cognitive Science Perspectives2019In: 14th International Conference on Spatial Information Theory / [ed] Sabine Timpf, Christoph Schlieder, Markus Kattenbeck, Bernd Ludwig and Kathleen Stewart, Dagstuhl, Germany, 2019, Vol. 142, p. 19:1-19:11Conference paper (Refereed)
    Abstract [en]

    With the development of modern geovisual analytics tools, several researchers have emphasized the importance of understanding users' cognitive, perceptual, and affective tendencies for supporting spatial decisions with geographic information displays (GIDs). However, most recent technological developments have focused on support for navigation in terms of efficiency and effectiveness while neglecting the importance of spatial learning. In the present paper, we will envision the future of GIDs that also support spatial learning in the context of large-scale navigation. Specifically, we will illustrate the manner in which GIDs have been (in the past) and might be (in the future) designed to be context-responsive, personalized, and supportive for active spatial learning from three different perspectives (i.e., GIScience, cartography, and cognitive science). We will also explain why this approach is essential for preventing the technological infantilizing of society (i.e., the reduction of our capacity to make decisions without technological assistance). Although these issues are common to nearly all emerging digital technologies, we argue that these issues become especially relevant in consideration of a person's current and future locations.

  • 10.
    Winter, Stephan
    et al.
    The University of Melbourne.
    Tomko, Martin
    The University of Melbourne.
    Vasardani, Maria
    RMIT.
    Richter, Kai-Florian
    Umeå University.
    Khoshelham, Kouroush
    The University of Melbourne.
    Kalantari, Mohsen
    The University of Melbourne.
    Infrastructure-Independent Indoor Localization and Navigation2019In: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 52, no 3, article id 61Article in journal (Refereed)
    Abstract [en]

    In the absence of any global positioning infrastructure for indoor environments, research on supporting human indoor localization and navigation trails decades behind research on outdoor localization and navigation. The major barrier to broader progress has been the dependency of indoor positioning on environment-specific infrastructure and resulting tailored technical solutions. Combined with the fragmentation and compartmentalization of indoor environments, this poses significant challenges to widespread adoption of indoor location-based services. This article puts aside all approaches of infrastructure-based support for human indoor localization and navigation and instead reviews technical concepts that are independent of sensors embedded in the environment. The reviewed concepts rely on a mobile computing platform with sensing capability and a human interaction interface (“smartphone”). This platform may or may not carry a stored map of the environment, but does not require in situ internet access. In this regard, the presented approaches are more challenging than any localization and navigation solutions specific to a particular, infrastructure-equipped indoor space, since they are not adapted to local context, and they may lack some of the accuracy achievable with those tailored solutions. However, only these approaches have the potential to be universally applicable.

  • 11.
    Winter, Stephan
    et al.
    Department of Infrastructure Engineering, University of Melbourne.
    Tomko, Martin
    Department of Infrastructure Engineering, University of Melbourne.
    Vasardani, Maria
    Department of Infrastructure Engineering, University of Melbourne.
    Richter, Kai-Florian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Koshelham, Kourosh
    Department of Infrastructure Engineering, University of Melbourne.
    Indoor localization and navigation independent of sensor based technologies2017Report (Other academic)
    Abstract [en]

    In this short article we present concepts of indoor localization and navigation that are independent of sensors embedded in the environment, and thus, standing against the tide of technology-based indoor localization. The motivation for doing so is clear: We seek solutions that are independent of particular environments, and thus globally applicable.

  • 12.
    Çöltekin, Arzu
    et al.
    Department of Geography, University of Zurich.
    Francelet, Rebecca
    Department of Geography, University of Zurich.
    Richter, Kai-Florian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Thoresen, John
    Laboratory of Behavioural Genetics, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL).
    Fabrikant, Sara Irina
    Department of Geography, University of Zurich.
    The effects of visual realism, spatial abilities, and competition on performance in map-based route learning in men2018In: Cartography and Geographic Information Science, ISSN 1523-0406, E-ISSN 1545-0465, Vol. 45, no 4, p. 339-353Article in journal (Refereed)
    Abstract [en]

    We report on how visual realism might influence map-based route learning performance in a controlled laboratory experiment with 104 male participants in a competitive context. Using animations of a dot moving through routes of interest, we find that participants recall the routes more accurately with abstract road maps than with more realistic satellite maps. We also find that, irrespective of visual realism, participants with higher spatial abilities (high-spatial participants) are more accurate in memorizing map-based routes than participants with lower spatial abilities (low-spatial participants). On the other hand, added visual realism limits high-spatial participants in their route recall speed, while it seems not to influence the recall speed of low-spatial participants. Competition affects participants’ overall confidence positively, but does not affect their route recall performance neither in terms of accuracy nor speed. With this study, we provide further empirical evidence demonstrating that it is important to choose the appropriate map type considering task characteristics and spatial abilities. While satellite maps might be perceived as more fun to use, or visually more attractive than road maps, they also require more cognitive resources for many map-based tasks, which is true even for high-spatial users.

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